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Microfinance

The poor have little or no collateral and cannot borrow against their future income because they tend not to have steady jobs or income streams that can be tracked. In addition, dealing with small transactions is costly for financial institutions. Microfinance –specialized institutions that serve the poor − tries to overcome these problems in innovative ways. Loan officers come from similar social strata as borrowers and often go to the poor instead of waiting for the poor to come to them. Microcredit also provides education as it provides credit. For example, group lending schemes improve repayment incentives and monitoring through peer pressure, and are also a way of building support networks and educating borrowers.

This part of our research program has two components. In the first, we use accounting data from leading microfinance institutions (MFIs) to investigate the trade-offs they face and the policies that may improve their performance and outreach to the poor. In the second, we evaluate the impact of new financial products offered by microfinance institutions via randomized trials.

To illustrate the first part of this research program, Fig. 1 shows that patterns of average revenues and costs vary systematically by lending type among a sample of leading MFIs. Village banks − where each branch forms a single, large group and is given a degree of self-governance by the MFI− charge relatively high interest rates and face high costs. Costs outweigh interest revenues, though, and the result is that the average return on assets (ROA) for village banks is negative. MFIs that offer loans to solidarity groups − contracts based on joint liability that are made to individuals, but for which the group shoulders responsibility if a member cannot repay −charge lower interest rates and face lower costs, but again costs exceed revenues and the average return on assets is –0.05. Only for MFIs that lend to individuals is the average return on assets positive, though small (0.01).

These patterns reflect differences in social mission, target customers, and location as much as management strategies. Summary statistics suggest, for example, that one reason that costs are so much higher for village banks and group lenders (relative to individual-based lenders) is that they make smaller-sized loans and serve poorer populations. Village banks, the least profitable lending type as a class, serve the poorest customers (as proxied by loan size) and their clients are more likely to be women. The customers of village banks and group lenders, for example, are largely women: 88% and 75%, respectively. In comparison, just under half of the customers of individual-based lenders are women (46%).

Village banks also make the smallest loans ($149 on average), followed by group lenders ($431). Individual-based lenders make far larger loans ($1220). Average loan size is often taken to be a proxy for the poverty of customers, and these results are in line with anecdotal evidence about the depth of outreach across lending types.

As microfinance becomes a popular tool for fighting poverty, institutions develop products and programs at a rapid pace. Policymakers and practitioners should know the relative impact of different products and programs, both to the client (in terms of welfare) and to the institution (in terms of financial sustainability). Our objective in this second part of the research program is to evaluate the impact of these innovations using randomized control trials.

There are several completed and on-going evaluations:

Agricultural extension – credit package in Kenya.Researchers evaluated DrumNet, a for-profit Kenyan NGO that encourages the adoption of export oriented crops by providing smallholder farmers with information about how to switch to export crops, with credit for purchase of the agricultural inputs, and with marketing services by then linking farmers directly to exporters.

Microfinance Lending MethodologiesFirst researchers created an experimental economics laboratory in a large urban market in Lima, Peru and over seven months conducted eleven different games that allowed them to investigate microfinance mechanisms in a systematic way.

In addition, researchers worked with a large rural bank in the Philippines (Green Bank of Caraga) to evaluate the role of group liability. Half of the 169 pre-existing group liability “centers” of approximately twenty women were randomly assigned to individual-liability centers (treatment) and the other half was kept as-is with group liability (control). Results indicate that the conversion to individual liability did not change the repayment rate, but that it led to higher growth in center size by both keeping more pre-existing borrowers and attracting new ones.

An explanation for this finding may be found in the response of new clients. In theory, there are two groups of borrowers that would join only individual liability centers. On one end of the distribution, bad risks would be screened out and rejected from group liability centers but could be accepted in individual liability centers if the bank is unable to screen as effectively. On the other end of the distribution, good risks may decide not to join group liability centers because they fear being forced to help other members repay more frequently than they will receive help. The left panel of Figure 1 plots the distribution of the number of times new clients had difficulty making their payments, while the right panel plots the same distributions for baseline clients (those borrowing at the time of conversion, hence screened under group liability). As the Figure shows, the distributions of baseline clients in treatment and control centers look alike, but the distribution of new clients in treatment centers is more concentrated around zero than that for control centers. This suggests that good risks were reluctant to join group liability centers but do so after these centers are converted to individual liability. We do not find evidence of bad risks also joining individual liability centers.

In an extension to this project, researchers are also working with the Green Bank as it opens new centers in new areas. The idea is to test whether the individual liability model performs as well when groups are initially formed under individual liability. Researchers are also introducing a hybrid design in which centers start as group liability but are told that conditional on successful repayment, they will convert to individual liability in the future.

In another extension, researchers are replicating the experiment in the Philippines with Pro Mujer Bolivia, a micro-lending NGO operating in several countries in Latin America.

Incentive Schemes for Credit OfficersResearchers are working with NRSP, a nation-wide MFI in Pakistan as they introduced a bonus scheme to reward (i) quality of the portfolio and (ii) quality of the community organizations in the village that are formed as part of the lending process.

Business Training and Loan SizesIn another field experiment with NRSP, some existing community organizations will receive business training while others will remain as is. In addition, a lottery will be introduced whereby borrowers can ask for larger loan sizes. Subject to NRSP approval, winners of the lottery will obtain the amounts approved by NRSP (that will be larger to the current limit). Losers of the lottery will obtain the current NRSP limit.

Social MobilizationIn the last field experiment with NRSP researchers will examine the role that social mobilization plays in empowering people and improving the delivery of basic public services. As NRSP starts operations in different villages, NRSP staff will arbitrarily target to mobilize (and organize into community organization) either 20 percent or 40 percent of the population.

Rainfall Insurance.Researchers are working with ICICI Lombard (insurance company) and BASIX (microfinance institution) in AP, India to evaluate a stand-alone weather insurance policy. Researchers conducted a baseline in 2004 and a follow-up in November, 2006. Using the 2004 data, researchers studied take-up of the rainfall insurance policy and found that it is decreasing in basis risk between insurance payouts and shocks to agricultural income, increasing in household wealth and decreasing in the extent to which credit constraints bind. These predictions match with a simple neoclassical model appended with borrowing constraints. Other patterns are less consistent with the ‘benchmark’ model. Risk averse households are found to be less, not more, likely to purchase insurance.

In addition, researchers are also conducting a field experiment that examines the impact of credit and rainfall insurance on the adoption of hybrid groundnut seeds. In particular, some farmers will be offered the bundle of credit with insurance to purchase seeds while others will be offered credit only. This allows an understanding of the differences as perceived by farmers between contingent and uncontingent credit.

Health Insurance.Researchers propose to evaluate the impact of the public health insurance system in the Philippines (PhilHealth) on group and individual-lending clients of Green Bank. The PhilHealth KaSAPI program offers potential costs and benefits whose tradeoffs are unknown. Potential benefits of introducing KaSAPI include improved client repayment, since anecdotal evidence suggests that illness of clients and their family members is one of the biggest causes of delinquency, improved client satisfaction and retention resulting from access to a valuable benefit (insurance) at a discounted rate. Potential costs of introducing KaSAPI include transaction costs of coordinating with PhilHealth, the requirement to purchase insurance which can be seen as a tax and may lead to increased drop outs among clients who are not interested in purchasing insurance, and the fact that clients who don’t purchase insurance under voluntary participation could be harmed if a greater presence of PhilHealth in their community undermines informal insurance networks. This evaluation will measure the cost and benefits of offering KaSAPI by conduction a randomized control trial with a compulsory PhilHealth KaSapi group (Treatment 1), a voluntary PhilHealth KaSapi group(Treatment 2) and a Control group.